16 Birth of the California Earthquake Authority (CEA) In California, homeowners insurance providers are required by law to offer earthquake coverage The 1994 M 6.7 Northridge earthquake caused a crisis Almost all insurance companies stopped providing homeowners insurance, which meant banks stopped providing mortgages The state stepped in and established the CEA, which is essentially a staterun earthquake reinsurance pool (they insure the insurance companies)

17 Birth of the California Earthquake Authority (CEA) In California, homeowners insurance providers are required by law to offer earthquake coverage The 1994 M 6.7 Northridge earthquake caused a crisis Almost all insurance companies stopped providing homeowners insurance, which meant banks stopped providing mortgages The state stepped in and established the CEA, which is essentially a staterun earthquake reinsurance pool (they insure the insurance companies) Who decides best available science? CEA is currently the largest earthquake insurance provider in the US (although only 12% of California homeowners have earthquake insurance) They are required by law to use best available science and any regional difference in insurance rates must be backed by science. They can also apply time-dependent probabilities since insurance rates are updated regularly.

18 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California UCERF UCERF UCERF3 (2014)

19 All models are wrong, some are useful (Box, 1979) More specifically: All models are an approximation of the system they represent

20 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California A better and better approximation UCERF UCERF UCERF3 (2014)

21 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California How do we build these models? UCERF UCERF UCERF3 (2014)

22

23 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California How do we build these models? UCERF UCERF UCERF3 (2014)

25 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California Earliest models based mostly on the geologic/paleoseismic perspective UCERF UCERF UCERF3 (2014)

26 Geology & Paleoseismology Perspective: Assume fault ruptures fully and only by itself (segmented/characteristic earthquake hypothesis) Compute magnitude from area ( e.g., M=4+log(Area) ) Compute frequency of rupture from slip-rate, or set as paleoseismically inferred event rate Assume Reid s (1910) elastic rebound theory, where probability drops after event and builds with time as tectonic stresses re-accumulate (probability depends on date of last event) Key Assumptions Earthquake recurrence intervals are decades to centuries; aftershocks regarded as small and negligible

27 Working Groups on California Earthquake Probabilities (WGCEPs) The most official time-dependent earthquake forecasts for California Earliest models based mostly on the geologic/paleoseismic perspective UCERF UCERF UCERF3 (2014)

37 USGS s Short-Term Earthquake Probability (STEP) Model Gerstenberger et al. (2005) Limitations: 1) Probability of triggering large damaging aftershock is independent of proximity to large faults 2) The is no elastic rebound Highest probability for any given rupture will be the moment after it occurs

38 USGS s Short-Term Earthquake Probability (STEP) Model Gerstenberger et al. (2005) Limitations: 1) Probability of triggering large damaging aftershock is independent of proximity to large faults 2) The is no elastic rebound 3) We d like synthetic catalogs of events rather than a mean forecast rate (e.g., to define complete distribution of possible losses rather than just mean value)

52 We pre-compute economic losses and fatalities for every UCERF3 rupture (~500,000) using an OpenSHA implementation of the HAZUS-MH methodology (Porter et al., 2012, SRL): Exposure for California single-family dwellings

53 We pre-compute economic losses and fatalities for every UCERF3 rupture (~500,000) using an OpenSHA implementation of the HAZUS-MH methodology (Porter et al., 2012, SRL): For a given ETAS simulation, we sum losses for all events that occurred in the synthetic catalog to get a loss estimate.

54 We pre-compute economic losses and fatalities for every UCERF3 rupture (~500,000) using an OpenSHA implementation of the HAZUS-MH methodology (Porter et al., 2012, SRL): For a given ETAS simulation, we sum losses for all events that occurred in the synthetic catalog to get a loss estimate. Repeat to obtain N different simulated catalogs

55 We pre-compute economic losses and fatalities for every UCERF3 rupture (~500,000) using an OpenSHA implementation of the HAZUS-MH methodology (Porter et al., 2012, SRL): For a given ETAS simulation, we sum losses for all events that occurred in the synthetic catalog to get a loss estimate. Repeat to obtain N different simulated catalogs Make a histogram of loss values, giving a probability distribution of possible values.

56 Not just mean expected loss Gains depend on forecast duration For single-family dwellings, but full inventory can also be used Fatalities also available

57 We now have an operationalizable, end-to-end system to forecast losses in California that: Relaxes segmentation and includes multifault ruptures Includes elastic rebound and spatiotemporal clustering Generates synthetic catalogs (stochastic event sets) Includes very efficient loss calculations

58 We now have an operationalizable, end-to-end system to forecast losses in California that: Relaxes segmentation and includes multifault ruptures Includes elastic rebound and spatiotemporal clustering Generates synthetic catalogs (stochastic event sets) Includes very efficient loss calculations This is required to get realistic results Otherwise ~85% of triggered large events would re-rupture the same fault (Field, 2012, SSA), which we don t see Leaving it out also produces doomsday sequences, and screws up Båth's Law. This is what has taken us so long

59 We now have an operationalizable, end-to-end system to forecast losses in California that: Relaxes segmentation and includes multifault ruptures Includes elastic rebound and spatiotemporal clustering Generates synthetic catalogs (stochastic event sets) Includes very efficient loss calculations All models are wrong, some are useful (Box, 1979)

60 We now have an operationalizable, end-to-end system to forecast losses in California. UCERF3 has assumptions, approximations, and corrections Every component will get a thorough vetting as we operationalize Your work is an important part of this effort

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